IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v12y2019i20p3849-d275437.html
   My bibliography  Save this article

Analysis of the Day-ahead Deviation Plan and Research on the Real-time Scheduling of Photovoltaic Greenhouses Based on Exergy Theory

Author

Listed:
  • Xiayun Duan

    (College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China)

  • Yifeng Ding

    (Electric Power Research Institute, State Grid Beijing Electric Power Company, Beijing 100075, China)

  • Huanna Niu

    (College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China)

  • Yuzhu Wang

    (College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China)

Abstract

For the correction problem of day-ahead plan deviation caused by energy prediction deviation in day-ahead scheduling stage of photovoltaic greenhouses, an exergy analysis method is used to propose the deviation model of heat required for photovoltaic greenhouses. Based on the deviation model, a real-time optimization scheduling model is established. The deviation model not only considers the non-negligible exergy loss during heating process of pipes, but also considers the difference between heat and thermal exergy affected by the actual indoor temperature. The goal of the real-time scheduling model is to minimize the absolute value of the difference between the energy supply and demand prediction deviation to be corrected and the adjustment of multi-form energy storage and electric loads, so that develop the real-time adjustment plan of energy storage and electric loads. The analysis results of the actual photovoltaic greenhouse show that of the heat required by a greenhouse based on the exergy theory calculation, the exergy loss of the heating process accounts for about 10%–20% of the total thermal exergy required and it cannot be ignored, so the calculation results can reflect the actual heat required more accurately and the greenhouse temperature is more suitable for plant growth. Moreover, the proposed real-time scheduling model can correct the deviation of the day-ahead plan and improve local consumption. The promotion ratio can reach 7%. Finally, the farmers’ electricity purchases cost is reduced. Thereby the effectiveness of the proposed heat deviation model and real-time scheduling model is verified.

Suggested Citation

  • Xiayun Duan & Yifeng Ding & Huanna Niu & Yuzhu Wang, 2019. "Analysis of the Day-ahead Deviation Plan and Research on the Real-time Scheduling of Photovoltaic Greenhouses Based on Exergy Theory," Energies, MDPI, vol. 12(20), pages 1-21, October.
  • Handle: RePEc:gam:jeners:v:12:y:2019:i:20:p:3849-:d:275437
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/12/20/3849/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/12/20/3849/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yuzhu Wang & Huanna Niu & Lu Yang & Weizhou Wang & Fuchao Liu, 2018. "An Optimization Method for Local Consumption of Photovoltaic Power in a Facility Agriculture Micro Energy Network," Energies, MDPI, vol. 11(6), pages 1-20, June.
    2. Ishaq, H. & Dincer, I., 2019. "Exergy analysis and performance evaluation of a newly developed integrated energy system for quenchable generation," Energy, Elsevier, vol. 179(C), pages 1191-1204.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yan Ren & Linmao Ren & Kai Zhang & Dong Liu & Xianhe Yao & Huawei Li, 2022. "Research on the Operational Strategy of the Hybrid Wind/PV/Small-Hydropower/Facility-Agriculture System Based on a Microgrid," Energies, MDPI, vol. 15(7), pages 1-15, March.
    2. Xin Zhang & Jianhua Yang & Weizhou Wang & Man Zhang & Tianjun Jing, 2018. "Integrated Optimal Dispatch of a Rural Micro-Energy-Grid with Multi-Energy Stream Based on Model Predictive Control," Energies, MDPI, vol. 11(12), pages 1-23, December.
    3. Wang, Haiyang & Zhang, Chenghui & Li, Ke & Ma, Xin, 2021. "Game theory-based multi-agent capacity optimization for integrated energy systems with compressed air energy storage," Energy, Elsevier, vol. 221(C).
    4. Ruiqiu Yao & Yukun Hu & Liz Varga, 2023. "Applications of Agent-Based Methods in Multi-Energy Systems—A Systematic Literature Review," Energies, MDPI, vol. 16(5), pages 1-36, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:12:y:2019:i:20:p:3849-:d:275437. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.